Embodiments of the invention relate generally to medical diagnostics and treatment assessment and, more particularly, to methods and systems for evaluating bone lesions using multi-modality image data.
It is not uncommon for a single patient to undergo a multitude of medical imaging exams, whether in a single doctor's visit, in a hospital stay, or even over the course of a lifetime. This is particularly likely when a patient undergoes a series of “tests” and scans to investigate a recently onset or previously undetected condition. It is increasingly common for a patient to be subjected to multiple scans across multiple medical imaging modalities because each exam can provide different pieces of information. For example, during a single doctor's visit or hospital stay, a magnetic resonance (MR) imaging system, an x-ray imaging system, or a computed tomography (CT) imaging system can be used to acquire images that provide anatomical information, while a positron emission tomography (PET) imaging system or functional MRI can be used to acquire images that provide functional information. The anatomical information providing insight into the anatomical makeup of the patient and the functional information providing insight into the functionality of a given anatomical structure, especially when subjected to a stimulus. Moreover, the combination of anatomical and functional information is not only advantageous in detecting a new pathology or abnormality, but the respective images, when taken over the course of an illness, for example, may show growth of lesions, responses to treatments, and disease progression. To assist in the analysis of anatomical and functional information, programs have been constructed that register an anatomical and a functional image thereby showing, in a single image, both anatomical and functional information.
Many clinical applications analyze 2D or 3D image data to perform and capture quantitative analytics. These include detection and sizing of lung nodules (Advanced Lung Analysis), quantification of vessel curvature, diameter, and tone (Advanced Vessel Analysis), cardiac vascular and function applications, navigating of the colon for detection of polyps (CT colonography), detection and sizing of lesions, and the like. Dedicated CT, MR, PET and nuclear medicine applications have been designed to output quantitative analytics from regions of interest (intensity, density (HU), standard uptake value (SUV), distances, volumes, growth rates, pattern and/or texture recognition, functional information, etc.) to help in the diagnosis and management of patients.
Quantification of bone lesions using medical images is an important aspect of clinical diagnostics and therapy. Information related to the quantity or overall volume of bone lesions detected in a patient may be used by medical practitioners to select the best course of treatment for a patient and to monitor treatment efficiency and collect relevant research data.
Conventional methods of quantifying bone lesions in a patient utilize a reference value as an estimate of the volume of a particular patient's skeletal structure. Because this reference value is a quantitative value selected from tabular reference data based on the demographics (e.g., age, sex, height, etc.) of the patient, the reference value may not accurately reflect the actual skeletal volume of the patient.
Lesions within the skeletal structure of the patient are detected by first manually segmenting the skeletal structure from image data acquired from the patient and manually identifying lesions within the segmentation. The manual segmentation of the skeletal structural and manual detection of lesions is very challenging due to the complexity of the skeletal structure. For example, the anatomy and composition of bone material can vary significantly among patients, which can lead to significant inter-operator variability.
Further, the segmentation of the skeletal structure typically includes the brain, which can cause inaccurate quantitative analytics of the skeletal structure, and in turn affects a practitioner's ability to efficiently and accurately acquire measurements and data to assess the patient's condition.
Therefore, it would be desirable to have a system and method of quantifying bone lesions that overcomes the aforementioned drawbacks.